The importance of Bayesian analysis has grown over the years due to development of Markov Chain Monte Carlo (MCMC) simulation methods, as well as the availability of affordable computing power. Bayesian analysis tends to be focused on the analysis of the so-called “posterior distribution,” and the MCMC simulation methods are able to produce approximate samples from this distribution. MCMC simulation methods may approximate a posterior distribution by generating approximate samples. The approximation may improve if the number of generated samples is large.